On the Notion of Cause
(1912)

Tools

"... The notion of time is ubiquitous in any activity that requires intelligence. In particular, several important notions like change, causality, action are described in terms of time. Therefore, the representation of time and reasoning about time is of crucial importance for many Artificial Intelligenc ..."

The notion of time is ubiquitous in any activity that requires intelligence. In particular, several important notions like change, causality, action are described in terms of time. Therefore, the representation of time and reasoning about time is of crucial importance for many Artificial Intelligence systems. Specifically during the last 10 years, it has been attracting the attention of many AI researchers. In this survey, the results of this work are analysed. Firstly, Temporal Reasoning is defined. Then, the most important representational issues which determine a Temporal Reasoning approach are introduced: the logical form on which the approach is based, the ontology (the units taken as primitives, the temporal relations, the algorithms that have been developed,. . . ) and the concepts related with reasoning about action (the representation of change, causality, action,. . . ). For each issue the different choices in the literature are discussed. 1 Introduction The notion of time i...

...wledge and providesthe set of TR functionalities presented above to asproblem solver.s1.3. Historical OverviewsWork on TR in AI has to be situated in the context of the philosophical theories of time =-=[48,87,s89,96,97,109,117]-=- intended to account for whatstime is. In AI the analysis and modelling of the notion of time started with several isolated application-oriented pieces of work like Bruce's Chronoss[16] for natural la...

... : + 2 NQ s N (43) Equation 42 might be called the Russell Map, as it resembles an argument illustrating the futility of basing a denition for determinism upon an equation of the form x(t) = f(x; t) [=-=128]-=-. It re
ects a fundamental limit on the interpretation of shadowing, and nicely questions even (blind) out-of-sample evaluation! is invoked in parameter estimation for perfect models (see, for example...

by
John McCarthy
- Philosophical Logic and Artificial Intelligence, 1990

"... This article discusses the problems and difficulties, the results so far, and some improvements in logic and logical languages that may be required to formalize common sense. Fundamental conceptual advances are almost certainly required. The object of the paper is to get more help for AI from philos ..."

This article discusses the problems and difficulties, the results so far, and some improvements in logic and logical languages that may be required to formalize common sense. Fundamental conceptual advances are almost certainly required. The object of the paper is to get more help for AI from philosophical logicians. Some of the requested help will be mostly philosophical and some will be logical. Likewise the concrete AI approach may fertilize philosophical logic as physics has repeatedly fertilized mathematics.

"... The ability to derive predictions for the outcomes of potential actions from observational data is one of the hallmarks of true causal reasoning. We present four learning experiments with deterministic and probabilistic data showing that people indeed make different predictions from causal models, w ..."

The ability to derive predictions for the outcomes of potential actions from observational data is one of the hallmarks of true causal reasoning. We present four learning experiments with deterministic and probabilistic data showing that people indeed make different predictions from causal models, whose parameters were learned in a purely observational learning phase, depending on whether learners believe that an event within the model has been merely observed (“seeing”) or was actively manipulated (“doing”). The predictions reflect sensitivity both to the structure of the causal models and to the size of their parameters. This competency is remarkable because the predictions for potential interventions were very different from the patterns that had actually been observed. Whereas associative and probabilistic theories fail, recent developments of causal Bayes net theories provide tools for modeling this competency. Causal knowledge underlies our ability to predict future events, to explain the occurrence of present events, and to achieve goals by means of actions. Thus, causal knowledge belongs to one of our most central cognitive competencies. However, the nature of causal knowledge has been debated. A number of philosophers and

"... This contribution explores Wolfgang Pauli’s idea that mind and matter are complementary aspects of the same reality. We adopt the working hypothesis that there is an undivided timeless primordial reality (the primordial “one world”). Breaking its symmetry, we ob-tain a contextual description of the ..."

This contribution explores Wolfgang Pauli’s idea that mind and matter are complementary aspects of the same reality. We adopt the working hypothesis that there is an undivided timeless primordial reality (the primordial “one world”). Breaking its symmetry, we ob-tain a contextual description of the holistic reality in terms of two categorically different domains, one tensed and the other tenseless. The tensed domain includes, in addition to tensed time, nonma-terial processes and mental events. The tenseless domain refers to matter and physical energy. This concept implies that mind cannot be reduced to matter, and that matter cannot be reduced to mind. The non-Boolean logical framework of modern quantum the-ory is general enough to implement this idea. Time is not taken to be an a priori concept, but an archetypal acausal order is as-sumed which can be represented by a one-parameter group of au-tomorphisms, generating a time operator which parametrizes all processes, whether material or nonmaterial. The time-reversal sym-metry is broken in the nonmaterial domain, resulting in a universal direction of time for the material domain as well.

"... Directed acyclic graph (DAG) models are popular tools for describing causal relationships and for guiding attempts to learn them from data. In particular, they appear to supply a means of extracting causal conclusions from probabilistic conditional independence properties inferred from purely observ ..."

Directed acyclic graph (DAG) models are popular tools for describing causal relationships and for guiding attempts to learn them from data. In particular, they appear to supply a means of extracting causal conclusions from probabilistic conditional independence properties inferred from purely observational data. I take a critical look at this enterprise, and suggest that it is in need of more, and more explicit, methodological and philosophical justification than it typically receives. In particular, I argue for the value of a clean separation between formal causal language and intuitive causal assumptions.

"... it is not useful: it is “a relic of a bygone age, surviving, like the monarchy, only because it is erroneously supposed to do no harm. ” His argument for this was that the kind of physical theories that we have come to regard as fundamental leave no place for the notion of causation: not only does t ..."

it is not useful: it is “a relic of a bygone age, surviving, like the monarchy, only because it is erroneously supposed to do no harm. ” His argument for this was that the kind of physical theories that we have come to regard as fundamental leave no place for the notion of causation: not only does the word ‘cause ’ not appear in the advanced sciences, but the laws that these sciences state are incompatible with causation as we normally understand it. But Nancy Cartwright has argued [1979] that abandoning the concept of causation would cripple science; her conclusion was based not on fundamental physics, but on more ordinary science such as the search for the causes of cancer. She argues that Russell was right that the fundamental theories of modern physics say nothing, even implicitly, about causation, and concludes on this basis that such theories are incomplete. It is with this cluster of issues that I will begin my discussion. Russell’s claim that the notion of causation is not needed in fundamental physics has been disputed by Earman [1976], but I think Russell is right and Earman wrong. Earman mentions various causal concepts in physics: determinism, causal signals, and microcausality. But determinism is explainable without the notion of causation, as both

"... The paper spells out five different accounts of the relationship between objects and relations three of which are versions of ontic structural realism (OSR). We argue that the distinction between objects and properties, including relations, is merely a conceptual one by contrast to an ontological on ..."

The paper spells out five different accounts of the relationship between objects and relations three of which are versions of ontic structural realism (OSR). We argue that the distinction between objects and properties, including relations, is merely a conceptual one by contrast to an ontological one: properties, including relations, are modes, that is the concrete, particular ways in which objects exist. We then set out moderate OSR as the view according to which irreducible relations are central ways in which the fundamental physical objects exist. Physical structures thus consist in objects for whom it is essential that they are related in certain ways. There hence are objects, but they do not possess an intrinsic identity. This view can also admit intrinsic properties as ways in which objects exist provided that these do not amount to identity conditions for the objects. Finally, we indicate how this view can take objective modality into account. In a first approach, ontic structural realism (OSR) is a realism towards physical structures in the sense of networks of concrete physical relations, without these relations being dependent

"... For a long time, regularity accounts of causation have virtually vanished from the scene. Problems encountered within other theoretical frameworks have recently induced authors working on causation, laws of nature, or methodologies of causal reasoning – as e.g. ..."

For a long time, regularity accounts of causation have virtually vanished from the scene. Problems encountered within other theoretical frameworks have recently induced authors working on causation, laws of nature, or methodologies of causal reasoning – as e.g.